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data scientist (Seattle, WA - U.S.)

Starbucks

Salary not specified
Oct 24, 2025
Seattle, WA, United States of America
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Starbucks is looking to solve business challenges and improve decision-making by leveraging data science to develop, enhance, and maintain analytical models and optimization algorithms. The goal is to translate complex analyses into actionable business insights to empower leaders.

Requirements

  • Proficiency in coding languages for data preparation and modeling, including SQL for querying large datasets and Python for building pipelines and statistical models
  • Solid understanding of statistical concepts, and techniques, such as regression, classification, decision trees, clustering, and causal inference, with practical experience applying them to real-world problems
  • Experience with data visualization tools and techniques (e.g., Tableau, Power BI) to communicate insights effectively to technical and non-technical audiences
  • Demonstrated curiosity and analytical rigor, with a strong ability to explore complex datasets, identify patterns, and generate actionable insights
  • Familiarity with PySpark and Databricks for distributed data processing and scalable analytics in cloud environments and advanced analytical workflows
  • Familiarity with geospatial analytics
  • Familiarity with operations research and Linear Programming

Responsibilities

  • Conduct Exploratory Data Analysis - Analyze large-scale datasets through data wrangling, feature engineering, and statistical exploration.
  • Build reusable data pipelines using tools such as Pandas, Databricks SQL, and Spark to uncover trends, prepare raw data for modeling, and generate actionable insights.
  • Design, enhance, and sustain statistical/analytical models tailored to specific domains such as store testing and experimentation, store development, supply chain, and marketing.
  • Leverage historical data, domain attributes, and external signals to develop models that address diverse business challenges and improve decision-making.
  • Partner with teams across data engineering, operations, product, supply chain, and more to translate business needs into scalable data science solutions.
  • Provide data-driven recommendations to senior leaders, contributing to long-term strategies and business roadmaps.
  • Tackle complex problems with intellectual curiosity, continuously explore new features and methodologies, and stay up-to-date with industry trends and best practices.

Other

  • Minimum of 1 year of experience
  • Excellent attention to detail, along with strong written and verbal communication skills to collaborate across cross-functional teams and present findings to stakeholders
  • We believe we do our best work when we're together, which is why we're onsite four days a week.